Model Card for kkk662/histrin-gpt-model

This is a fine-tuned GPT model specialized for technical text in Korean, focusing on railway systems and signaling mechanisms.

Model Details

Model Description

This model is fine-tuned on technical documentation related to railway systems, using a dataset that includes both text and tables extracted from PDFs. It is designed to understand and generate precise Korean technical text.

• Developed by: kkk662
• Funded by (optional): Internal Research
• Shared by (optional): kkk662
• Model type: GPT-Neo 1.3B
• Language(s) (NLP): Korean, English
• License: Apache 2.0
• Finetuned from model (optional): EleutherAI/gpt-neo-1.3B

Model Sources [optional]

• Repository: https://huggingface.co/kkk662/histrin-gpt-model
• Paper [optional]: N/A
• Demo [optional]: N/A

Uses

Direct Use

This model can be directly used for generating technical descriptions, explanations, and summaries related to railway systems in Korean.

Downstream Use [optional]

The model can be fine-tuned further for domain-specific tasks, such as creating operation manuals or translating technical documents into Korean.

Out-of-Scope Use

This model is not suitable for general-purpose NLP tasks outside the technical domain.

Bias, Risks, and Limitations

Recommendations

Users should be aware that the model's performance is highly domain-specific. Misuse in non-technical or unrelated domains may lead to inaccurate or nonsensical results.

How to Get Started with the Model

Use the code below to get started with the model:

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "kkk662/histrin-gpt-model"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

input_text = "한국 고속철도 시스템대해 설명해줘."
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_length=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))